Colon cancer combined with obesity indicates improved survival- research on relevant mechanism

Abstract

Obesity contributes to the incidence of various tumors, including colon cancer. However, the impact of obesity on patients' survival and related mechanisms remains unclear. Multi-omics data of 227 cases of colon cancer patients combined with clinical characteristics data were acquired from The Cancer Genome Atlas (TCGA) database. We confirmed obesity as an independent prognostic factor for improved overall survival of colon cancer patients. We demonstrated that hypoxia pathways were repressed in obese patients by regulating miR-210. Immune checkpoints PD-1 and LAG3 were also downregulated in obese patients, which indicated enhanced immune surveillance. The frequency of PIK3CA and KRAS mutations was decreased in obese patients. The sites and types of TP53 mutation were alternated in obesity patients. In conclusion, our research demonstrated the potential mechanisms of prolonged survival in colon cancer patients combined with obesity, which may provide potential value for improving the prognosis of colon cancer.

Keywords: TP53; colon cancer; hypoxia; immune checkpoints; obesity.

Figure 1

Obesity is an independent prognostic factor for improved overall survival. (A) The association of BMI and Overall Survival (OS) performed by Kaplan-Meier analysis. Patients were divided into 3 groups according to WHO standard (normal weight: BMI<25, overweight: 25≤BMI<30 and obesity: BMI≥30 kg/m²). (B) All patients redistributed into 2 groups (combined normal weight and overweight patients as normal group: BMI<30 vs obesity group: BMI≥30 kg/m²) and performed by Kaplan-Meier analysis. (C) Disease-Free Survival of normal group and obesity group performed by Kaplan-Meier analysis. (D) Progression-Free Survival of normal group and obesity group performed by Kaplan-Meier analysis. (E) Risk factors of OS analyzed by univariate Cox regression model. (F) Risk factors of OS analyzed by multivariate Cox regression model. (^*p<0.05, ^**p<0.01, ^***p<0.001).

Figure 2

Differentially expressed genes in obesity patients are closely related to tumor regulation. (A) Differentially expressed genes (DEGs) between obesity and normal groups. (B) Gene Ontology (GO) analysis of DEGs. (C) KEGG pathway analysis of DEGs. (D) Protein-protein interaction (PPI) analysis of DEGs.

Figure 3

Obesity was associated with repressed hypoxia in colon cancer via inhibiting miR-210. (A) Differentially expressed miRNAs (DEMs) between obesity and normal groups. (B) The relationship of OS and miR-210 (divided by median of expression) performed by Kaplan-Meier analysis. (C) KEGG pathway analysis of miR-210-targeted genes (predicted by TargetScan database). (D) GO analysis of miR-210-targeted genes. (E) Hypoxia score of obesity and normal groups, derived from three different hypoxia scoring systems (Ragnum, Winter, Buffa hypoxia system). (F) The correlation of miR-210 and 3 different hypoxia scores analyzed by Pearson Correlation Coefficient. (G) Differentially expressed proteins between obesity and normal groups derived from Reverse Phase Protein Arrays (RPPA) data. (H) The invasion and migration ability of HCT-116 cells under hypoxia and normoxia. (I) The proliferation ability of HCT-116 cells under hypoxia and normoxia. (J) The expression of hypoxia associated genes of HCT-116 cells under hypoxia and normoxia. (^*p<0.05, ^**p<0.01, ^***p<0.001).

Figure 4

Obesity was associated with the alteration of gene mutations. (A) Forest plot for different mutations frequency compared between normal and obesity groups, analyzed by Chi-square test. (B) Top 10 mutations in normal and obesity groups. (C) “Lollipop” graph for specific mutation frequency, types and sites in PIK3CA, KRAS and TP53 (p53) protein domain. Mutation sites were shown on the x-axis, and the frequency of a particular mutation was represented by the height (y-axis). (D) Interaction of each top 10 mutation in normal and obesity group analyzed by Fisher exact test. (E) The distribution of copy number variation (CNV) in normal and obesity groups analyzed by Chi-square test. (^*p<0.05, ^**p<0.01, ^***p<0.001).

Figure 5

Obesity was associated with repression of immune checkpoints. (A) The expression of various immune checkpoints in obesity and normal groups. (B) The expression of LAG3 and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. (C) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. (D) The correlation matrix of each immune checkpoint in obesity and normal group. (^*p<0.05, ^**p<0.01).